Arnoud V. den Boer

Management Science and Operations Research · 2013

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 30 citations into it; #4,974 of 11,946 by trust here, #10,893 by citations
• Marketing — 26 citations into it; #2,208 of 6,289 by trust here, #6,049 by citations
• Management Information Systems — 22 citations into it; #1,090 of 3,376 by trust here, #3,104 by citations
• Economics and Econometrics — 15 citations into it
• Artificial Intelligence — 7 citations into it
• Strategy and Management — 7 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Arnoud V. den Boer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Robert D. Kleinberg
2. Frank Thomson Leighton
3. Xuanming Su
4. Omar Besbes
5. Paat Rusmevichientong
6. Assaf J. Zeevi
7. Nicolò Cesa-Bianchi
8. T. L. Lai Andherbertrobbins
9. Aleksandrs Slivkins
10. Frank M. Bass

Who trusts Arnoud V. den Boer overall

1. Ashwinkumar Badanidiyuru
2. Aleksandrs Slivkins
3. Robert D. Kleinberg
4. Graziano Abrate

Papers from Arnoud V. den Boer's perspective

Ordered by how strongly the researchers Arnoud V. den Boer trusts endorse each paper. Same corpus, a different order for every researcher.

1. The value of knowing a demand curve: bounds on regret for online posted-price auctions (44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings.)
2. Finite-time Analysis of the Multiarmed Bandit Problem
3. Asymptotically efficient adaptive allocation rules
4. Some aspects of the sequential design of experiments
5. Asymptotically Efficient Adaptive Allocation Rules
6. Information Theory: 1948-1998 - Guest Editorial
7. Multi-armed Bandit Allocation Indices
8. Using Confidence Bounds for Exploitation-Exploration Trade-offs
9. Online Convex Programming and Generalized Infinitesimal Gradient Ascent
10. Online convex optimization in the bandit setting: gradient descent without a gradient

Their papers

• Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions (2013) — 523 citations